python inference.py --img-path /Path/To/Image --dataset Model_Type

--model - choose from "icnet"/"pspnet"/"fcn"/"enet"  

from model import FCN8s, PSPNet50, ICNet, ENet

model = PSPNet50() # or another model

model.read_input(img_path)  # read image data from path

sess = tf.Session(config=config)
init = tf.global_variables_initializer()
sess.run(init)

model.load(model_path, sess)  # load pretrained model
preds = model.forward(sess) # Get prediction 

@inproceedings{zhao2017pspnet,
  author = {Hengshuang Zhao and
            Jianping Shi and
            Xiaojuan Qi and
            Xiaogang Wang and
            Jiaya Jia},
  title = {Pyramid Scene Parsing Network},
  booktitle = {Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017}
}

@inproceedings{zhou2017scene,
    title={Scene Parsing through ADE20K Dataset},
    author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
    booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
    year={2017}
}

@article{zhou2016semantic,
  title={Semantic understanding of scenes through the ade20k dataset},
  author={Zhou, Bolei and Zhao, Hang and Puig, Xavier and Fidler, Sanja and Barriuso, Adela and Torralba, Antonio},
  journal={arXiv preprint arXiv:1608.05442},
  year={2016}
}